Overview
This endpoint allows you to submit multiple search queries in a single request, enabling efficient batch processing of search operations. It’s ideal for applications that need to search for many terms simultaneously, such as data processing pipelines, bulk concept mapping, or batch validation workflows.Request Body
Array of search query objects
Query Parameters
Processing mode for queries
Options:
Options:
parallel
, sequential
, adaptive
Merge similar results across queries
Include performance statistics for each query
How to handle individual query failures
Options:
Options:
continue
, stop_on_first
, stop_on_threshold
Maximum number of failed queries before stopping batch processing. Only used when failure_handling is set to stop_on_threshold.
Valid range: Zero or greater
Behavior: Zero disables the threshold. Any positive value activates the threshold.
Represents the absolute count of failures allowed.
Valid range: Zero or greater
Behavior: Zero disables the threshold. Any positive value activates the threshold.
Represents the absolute count of failures allowed.
Maximum processing time for the entire batch (max 300)
Processing priority
Options:
Options:
low
, normal
, high
, urgent
Specific vocabulary release version (defaults to latest)
Response
Indicates if the batch request was successful
Usage Examples
Basic Bulk Search
Search multiple terms simultaneously:Advanced Bulk Search with Different Parameters
Use different search parameters for each query:High-Volume Processing
Process large batches with optimized settings:Consolidated Results
Get merged results across all queries:Error Handling
Configure how to handle query failures:Processing Modes
Parallel Processing
- Description: Execute all queries simultaneously
- Benefits: Fastest processing for independent queries
- Best For: Small to medium batches (less than 100 queries)
- Trade-offs: Higher resource usage
Sequential Processing
- Description: Execute queries one at a time
- Benefits: Lower resource usage, predictable performance
- Best For: Large batches, resource-constrained environments
- Trade-offs: Slower overall processing time
Adaptive Processing
- Description: Automatically choose optimal processing strategy
- Benefits: Balances speed and resource usage
- Best For: Variable query complexity, mixed batch sizes
- Trade-offs: Slight overhead for decision making
Search Types in Bulk Operations
Exact Search
- Performance: Fastest processing
- Accuracy: Highest precision
- Use Case: Known terms, validation workflows
Fuzzy Search
- Performance: Moderate processing time
- Accuracy: Handles typos and variations
- Use Case: User input, OCR text processing
Semantic Search
- Performance: Slower processing
- Accuracy: Contextual understanding
- Use Case: Natural language queries, concept discovery
Phonetic Search
- Performance: Moderate processing time
- Accuracy: Handles pronunciation variations
- Use Case: Voice input, international terms
Optimization Strategies
Query Grouping
- Group Similar Vocabularies: Combine queries targeting same vocabularies
- Domain Clustering: Group queries by medical domain
- Search Type Batching: Batch similar search types together
Performance Tuning
- Limit Results: Use appropriate max_results values
- Score Thresholds: Set min_score to filter low-quality matches
- Vocabulary Selection: Limit to relevant vocabularies only
Resource Management
- Batch Size: Optimal batch size is 10-50 queries
- Timeout Settings: Allow sufficient time for complex queries
- Priority Levels: Use higher priority for time-sensitive requests
Error Handling Strategies
- Continue on Error: Process all valid queries despite failures
- Fail Fast: Stop processing on first error for validation workflows
- Threshold-based: Stop when error rate exceeds acceptable level
Related Endpoints
- Basic Search - Single query search
- Advanced Search - Complex search with filters
- Semantic Search - Contextual search
- Search Concepts - Concept-specific search